LaLegumbreArtificial
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End of training
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9941275167785235
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0113
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- Accuracy: 0.9941
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.0374 | 0.9954 | 162 | 0.0350 | 0.9866 |
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| 0.0233 | 1.9969 | 325 | 0.0258 | 0.9891 |
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| 0.0253 | 2.9985 | 488 | 0.0188 | 0.9916 |
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| 0.0103 | 4.0 | 651 | 0.0283 | 0.9908 |
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| 0.0065 | 4.9770 | 810 | 0.0113 | 0.9941 |
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### Framework versions
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